Alzheimer’s Disease Detection from Retinal Images Using Machine Learning and Deep Learning Techniques: A Perspective

Adilet Uvaliyev, Leanne Lai Hang Chan*

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

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Abstract

Alzheimer’s disease (AD) is a neurodegenerative disease that results in a loss of cognitive functions. The early discovery of it can potentially stop or decrease the severity of AD. Extensive research has been conducted to find AD biomarkers. In recent years, due to the development of AI technologies and the ease of obtaining retinal images, various machine learning (ML)- and deep learning (DL)-based methods of identifying AD patients from these images have been proposed. These models are significant as they represent a potential screening tool for AD and a tool for identifying biomarkers from retinal images. This paper reviews the recent progress in this direction. It presents an overview of relevant methods and analyzes their strengths and limitations. Also, it discusses common challenges and possible future directions related to this topic. © 2025 by the authors.
Original languageEnglish
Article number4963
JournalApplied Sciences (Switzerland)
Volume15
Issue number9
Online published30 Apr 2025
DOIs
Publication statusPublished - May 2025

Funding

This work was supported by the City University of Hong Kong (7020058).

Research Keywords

  • Alzheimer’s disease
  • deep learning
  • machine learning
  • retinal images

Publisher's Copyright Statement

  • This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/

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